For most businesses, quality is the centre piece for the entire organization. Without quality practices, your deliverables many never be validated or accepted by the client, thus resulting in a delayed or lost project. Some of the reasons may be a late or sub standard product, or service, but more or less these issues often arise from infective processes.
In an age where we receive much more data than we can successfully evaluate, the term “garbage in garbage out” is more relevant than ever. The likelihood of an organization putting garbage into the system and thus bypassing useful data is much higher than in the past.
This isn’t to say that individual expertise should go unnoticed; it is just much easier to miss critical data when you’re already swamped by more information than you can effectively process. Here is where process mining can help.
In big data environments, we can search within your organization, speed up your process discovery methods, show you your current processes, and identify key areas where quality can be improved. Sometimes it takes a fresh pair of eyes, coupled with the right tools, to help highlight the right information from the “garbage” often put in the system.
With our know-how and data process mining techniques we can improve customer satisfaction as well as limit the amount of process weaknesses found in your company. So, while analyzing big data processes, we can deal with both quality control which seeks out these deficiencies, as well as quality assurance which simultaneously tackles these problems to improve quality within your organization.
This will ensure you no longer put “garbage” into the system and improve your internal business quality which will naturally transfer over to look past traditional methods into more substantial data analysis.